The field of the invention is gated computerized tomography (CT) imaging and more specifically methods and apparatus that correct for missed R-peak detections, erroneously identified R-peak detections and shifted R-peak detections.
Many different types of medical imaging systems have been developed that are used for different purposes. Perhaps the most common type of imaging system category includes X-ray systems wherein radiation is directed across a portion of a patient to be imaged and toward a detector panel. An exemplary X-ray detector panel includes a Csl scintillator coupled with an amorphous silicon array. With radiation directed toward a region of a patient to be images (i.e., a region of interest), the region of interest blocks some of the radiation and some of the radiation passes through the region and is collected by the panel. The amount of radiation that passes through the region along the trajectory of a given radiation ray depends upon the type of tissue along the trajectory. Thus, a tumor may block more radiation than flesh and bone may block more radiation than a tumor and so on. Hence X-ray system can be used to collect a “projection” through a patient.
While useful, simple X-ray systems have many limitations. One important limitation to X-ray imaging systems is that such systems, as described above, only provide side projections through a region and cannot be used to generate other useful images such as “slice” images (i.e., images perpendicular to projection images) through a region of interest. For instance, an exemplary useful slice image may include a slice image through a patient's heart.
Another type of imaging system that is useful in generating slice images is generally referred to as a computerized tomography (CT) system. An exemplary CT system includes a radiation source and a radiation detector mounted on opposite sides of an imaging area where the imaging area is centered along a translation or Z-axis. The source generates radiation that is collimated into a beam including a plurality of radiation rays directed along trajectories generally across the imaging area. A line detector may be positioned perpendicular to the Z-axis to collect slice image data during a data acquisition period.
During an acquisition period a region of interest is positioned within the imaging area and, with the radiation source turned on, the region of interest blocks some of the radiation and some of the radiation passes through the region and is collected by the line detector. As in X-ray systems, the amount of radiation that passes through the region of interest along the trajectory of a given radiation ray is dependent upon the type of tissue along the trajectory. In CT systems the source and line detector are rotated about the region of interest within a rotation plane through the region of interest so that radiation “projections” can be collected for a large number of angles about the region. By combining the projections corresponding to a slice through the region of interest using a filtering and back projecting technique, a two-dimensional tomographic or axial image (i.e., a slice image) of the slice is generated.
While some diagnostic techniques only require one or a small number of slice images, many techniques require a large number of parallel CT slice images. For example, some techniques require examination of many parallel images to identify where an arterial blockage begins and ends and the nature of the blockage there between. As another example, many techniques reformat two dimensional data into, in effect, three dimensional volumetric images, that can be sliced and diced in several different directions so that various image planes can be employed. For instance, where two dimensional data is acquired for transverse or cross sectional slices through a three dimensional region of interest (e.g., through a patient's torso), the data may be reformatted to generate sagital (i.e., the side plane passing through the long axis of the body) or coronal (i.e., the frontal plane passing through the long axis of the body) images through the region of interest.
In order to generate several slice images rapidly, CT detectors are typically configured having several parallel detector rows such that, during a single rotation about the imaging area, each detector row collects data that can subsequently be used to generate a separate CT slice image.
While increasing the number of detector rows reduces acquisition time, detector elements are relatively expensive and thus more rows translates into a more costly overall system. As a balance between cost and speed, most multi-row detectors include less than 10 detector rows. Hereinafter it will be assumed that an exemplary detector includes eight detector rows.
Where a detector includes eight rows and more than eight slice images are required, several different acquisition periods are typically used to acquire the necessary slice image data. For instance, assume that 80 slice images (an admittedly small number but sufficient for exemplary purposes) through a ROI are required. In this case, the ROI may be divided into ten separate sub-volumes, each of the ten sub-volumes corresponding to a separate eight of the 80 required slice images. Thereafter, ten separate acquisition periods may be used to collect the sets of slice image data corresponding to the ten sub-volumes, data corresponding to eight separate slice images collected during each of the ten separate acquisition periods.
It has been found that, for large volumes or ROIs, data necessary to generate many parallel thin slice images can be acquired most rapidly by helically collecting the data. To this end, while the source and detector are rotated about the imaging area, a patient bed is translated there through so that the radiation fan beam sweeps a helical path through the ROI. After helical data is collected, the data is converted to slice image data by any of several different weighting and filtering processes and thereafter the slice image data is back projected to form the viewable image.
In the case of helically acquired and stored raw data, the data can be used to construct virtually any number of slice images through a corresponding ROI. For instance, despite using a detector having eight rows of elements to collect helical data, the data may be processed to generate 16, 20, 500 or even thousands of separate slice images or, indeed, may be interpolated to generate a 3-D volumetric image, if desired.
In most imaging systems that generate still images, it is important that, to the extent possible, during data acquisition, the structure being imaged remain completely still. Even slight structure movement during acquisition can cause image artifacts in, and substantially reduce the diagnostic value of, resulting images. For this reason, during acquisition periods, patients are typically instructed to maintain the region of interest within the imaging area as still as possible by, for instance, holding the patient's breadth.
Despite a patient's attempts to control movement, certain anatomical structures cannot be held still and continue movement during acquisition periods. For instance, a patient's heart beats continually during data acquisition cycles and the beating movement complicates the process of acquiring diagnostic quality data.
In the case of the heart, fortunately, the beating cycle is repetitive and there are certain cycle phases during which the heart muscle is relatively at rest. As well known in the art, during a diastolic phase of the beating cycle when the heart is filling with blood, the heart is relatively at rest and movement is minimal. Thus, by restricting data acquisition periods to the diastolic phases of the heart beating cycle, relatively movement-free data can be acquired and used to generate CT slice images.
To this end, the industry has developed cardiac gated CT imaging systems. These systems generally take two different forms including shoot and move gating scans and retro-gating reconstructions. In the case of shoot and move scans, an electrocardiogram (EKG) system is used to monitor heart beating phase and to gate the acquisition of data so that data is only acquired during specific phases of the heart beating cycle (e.g., systolic, diastolic, etc.) Thereafter, the acquired data is used to generate slice images in a conventional manner.
In the case of retro-gating reconstruction, a full set of helical data is acquired and stored along with corresponding EKG signals. Thereafter, a heart cycle phase range is selected which indicates a range of the cycle for which images should be generated and an image reconstructor retrieves the helical data sub-set corresponding to the phase range from each heart cycle and generates the required images. Hereinafter the phrase “phase location” will be used to refer to as a phase point within a heart cycle and the phrase “phase range” will be used to refer to a range that is centered on a corresponding phase location.
In addition to minimizing movement related image artifacts, each of the EKG-gating processes (i.e., prospective and retrospective) is also meant to reduce mis-registration between sets of images that are generated using data corresponding to different sub-volumes of a region of interest. For instance, in the case above where a region is divided into ten separate sub-volumes and data for each sub-volume is collected during a separate acquisition period, if data for two consecutive sub-volumes is collected during different heart beating phases (i.e., during different phased of the heart cycles corresponding to the two consecutive sub-volumes), resulting images will likely be misaligned. Thus, by collecting data for all sub-volumes during similar heart beating phases, misalignment is substantially reduced.
In the cases of axially acquired data and helically acquired data this means restricting data to a specified phase range within each heart beating cycle. For instance, the acquired period may be between 70% and 80% of the total heart beating cycle where the cycles begin and end at peak cycle amplitudes. Hereinafter peak cycle amplitudes will be referred to as R-peaks and a heart beating cycle between two R-peaks will be referred to as an R-to-R interval.
Because EKG-gated reconstruction techniques are based on the cardiac R-to-R interval, it is critical that R-peak instances be precisely and accurately identified for each heart cycle. In practice, unfortunately, there are several sources of R-peak error in typical CT imaging systems that use gated techniques. For instance, patient arrhythmia such as premature ventricular contraction (PVC) has been known to throw off R-peak detection. As another instance, EKG line noise in some systems is appreciable and can cause R-peak errors. Moreover, the R-peak detection circuitry often has inherent limitations that result in R-peak errors.
R-peak detection errors have several consequences. For instance, when a heart beat occurs but an R-peak is not recorded, projection data corresponding to the missed heart cycle will not be available to generate an image at a corresponding selected location in space and time. As another instance, when an R-peak is recorded but does not correspond to an actual heart beat or is shifted in time with respect to a corresponding heart beat (i.e., an artificial R-peak), the phase location of an image generated using data corresponding to the artificial R-peak will be inaccurate. These R-peak errors cause discontinuities in the image series which are readily apparent in a coronal or a sagital view from a multi-planar reformat rendering.